Observation of contrast variations of a copper (Ⅱ) complex by scanning tunneling microscopy

This report presents experimental observations of dramatic variations in STM images of bis [1,3-DI(p-n-tetradecyloxyphenyl)propane-1,3-dionato]copper( Ⅱ） (abbreviated to C14O-Cu)physisorbed on HOPG as the bias voltage is changed .Several representative image patterns were obtained for the rich changes of the internal contrast of the molecule .Submolecular features of the molecular cores and the interdigitated alkyl parts are clearly visible.     

2D self-assembling of 4, 5-didodecylthiolphthalonitrile on graphite surface

An important precursor 4,5-didodecylthiolphthalonitrile (DCP) for synthesis of phthalocyanines (Pcs) and subphthalocyanines (SubPcs) was synthesized and the assembling structure of this molecule on the basal plane of highly oriented pyrolytic graphite (HOPG) surface was characterized using the scanning tunneling microscopy (STM) in ambient conditions. In high-resolution images of the molecules, we found that the arrangement of the cyano groups forms a “head-to-head” configuration to keep the stability of the entire system. The mismatch of the DCP molecules with the substrate lattice has also been observed in the experiment.     

ENTROPY,INFORMATION,NOISE—STUDIES ON SYSTEM EVOLUTION

Universe, ecosystem, social system, etc. are evolving systems. The evolving processes of thesesystems have gradual small changes and rapid drastic changes with uncertainties under the constraintsof environment. Systems, as a whole, are evolving toward complexity, diversity and variety withfluctuations and jumps. New order emerges from "mutations". The evolution is bothchance-dependent and path-dependent. In this paper three basics: entropy, information and noise areemphasized with regard to system evolution which is a field that can give people wisdom to solvesystem problems with domain knowledge.     

Burger''s方程的若干AGE方法

以求解Ｂｕｒｇｅｒ‘ｓ方程的中心差分格式,显示逆风格式,Ｓａｍａｒｓｋｉｉ格式及修正Ｄｅｎｎｉｓ格式为基础,构造了若干新的ＡＧＥ方法,讨论了方法的线性化稳定性数值结果表明,对于求解Ｂｕｒｇｅｒ’ｓ方程大Ｒｅｙｎｏｌｄ数问题,除了Ｃ－ＡＧＥ方法外,文中所构造的其他ＡＧＥ方法明显优于Ｅｖａｎｓ的分组显式方法。     

Separating Latent Classes by Information Criteria

This study evaluates performance of information criteria used to separate latent classes. In the evaluations, various numbers of latent classes, sample sizes, parameter structures and latent-class complexities were designed to simulate datasets. The average accuracy rates of information criteria in selecting the designed numbers of latent classes were the core results in this experiment. The study revealed that widely used information criteria, e.g., AIC, BIC, CAIC, could perform poorly under some circumstances. By including a sample size adjustment (Rissanen, 1978), the unsatis-factory performances could be improved considerably. The sample size adjustment provides a plausible solution for separating latent classes. Guidelines are provided to help achieve optimum use of the model fit indices.     

A situation calculus based approach to dynamic management of e-business services

In the era of e-businesses, the traditional business services are greatly challenged by the ever-increasing demands from customers with various backgrounds and personalities. Large numbers of new e-businesses are driven by the needs of customers. The existing dynamics inherent in the customer needs require the corresponding dynamic management of services. Attempting to respond to customers in a rapid and intelligent way, this paper proposes a situation calculus based approach for dynamically managing e-Business services in the ubiquitous environment. By employing the formalism of the situation calculus to enable intelligence and automation, the approach can implement. the functions of service automatic composition and model verification. These functions will improve the degree of customer-orientation and enable fast responsiveness in the emerging e-service systems.     

Conflict analysis approaches for investigating attitudes and misperceptions in the War of 1812

Formal systems engineering approaches to modeling misperceptions and attitudes are employed within the framework of the graph model for conflict resolution to systematically study the War of 1812 between the United States of America and Great Britain in order to provide enhanced insights into the causes of the war. More specifically, relational definitions for preferences, movements and stability concepts are defined for describing the attitudes and associated behavior of decision makers involved in a conflict. To capture misperceptions of decision makers in the War of 1812, attitudes are studied within the structure of a hypergame. Combining attitudes and misperceptions within the paradigm of the graph model furnishes the flexible analytical tool which demonstrates that misunderstanding of attitudes by Great Britain and the United States may have contributed to the outbreak of this nasty war.     

THE λ-GROBNER BASES UNDER POLYNOMIAL COMPOSITION

Polynomial composition is the operation of replacing variables in a polynomial with other polynomials. λ-Grgbner basis is an especial Grobner basis. The main problem in the paper is： when does composition commute with λ-Grobner basis computation？ We shall answer better the above question. This has a natural application in the computation of λ-Grobner bases.     

在校大学生消费情况分析及科学理财模式的构筑

通过问卷调查对在校大学生的消费结构现状进行了分析,指出目前大学生消费结构中存在的问题,提出从社会、家庭、学校、学生个人四个方面全方位构筑大学生科学的理财模式,以期对大学生合理消费模式的形成提供指导.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.